Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Coursera Project Network

Customer Segmentation using K-Means Clustering in R

Coursera Project Network via Coursera

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages.
By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing.
Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

Syllabus

  • Project Overview
    • Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages. By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing. Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

Taught by

Arimoro Olayinka Imisioluwa

Reviews

3.6 rating at Coursera based on 11 ratings

Start your review of Customer Segmentation using K-Means Clustering in R

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.